Evaluating the effects of mixed osteolytic/osteoblastic metastasis on vertebral bone quality in a new rat model

Spinal metastases often show mixed areas of enhanced (osteoblastic) bone growth adjacent to areas of thinning (osteolytic) bone. This study aims to quantitatively characterize bone quality and tumor burden within a new rat model of mixed osteolytic/osteoblastic spinal metastases. Mixed vertebral metastases were analyzed in nude rats 21‐days post intracardiac injection of Ace‐1 canine prostate cancer cells. Vertebral micro‐architecture was assessed in µCT images. Histologic processing quantified tumor burden (PTHrP), osteoclast activity (TRAP), and osteoid formation (Goldner's Trichrome) in ½ of all samples. Remaining samples were mechanically tested to failure in compression. Metastatically involved vertebrae exhibited extreme osteolysis, evident through an increase in osteoclasts leading to significantly reduced trabecular bone volume. Metastatically involved vertebrae also exhibited increased osteoid characteristic of osteoblastic lesions. While mechanical properties in tumor‐bearing vertebrae were not significantly decreased compared to controls, a strong correlation was found between trabecular volumetric BMD and ultimate force. The highly aggressive Ace‐1 skeletal metastases demonstrated predominant osteolysis with some areas of immature, new osteoblastic bone formation. Bone quality resulting from these lesions consisted of decreased structural properties, but without a significant impact on mechanical integrity. © 2011 Orthopaedic Research Society Published by Wiley Periodicals, Inc. J Orthop Res 30:817–823, 2012     

A spatio-temporal wavelet-chaos methodology for EEG-based diagnosis of Alzheimer's disease

A spatio-temporal wavelet-chaos methodology is presented for analysis of EEGs and their delta, theta, alpha, and beta sub-bands for discovering potential markers of abnormality in Alzheimer's disease (AD). The non-linear dynamics of the EEG and EEG sub-bands are quantified in the form of the correlation dimension (CD), representing system complexity, and the largest Lyapunov exponent (LLE), representing system chaoticity. The methodology is applied to two groups of EEGs: healthy subjects and AD patients. The eyes open and eyes closed conditions are investigated to evaluate the effect of visual input and attention. EEGs from different loci in the brain are investigated to discover areas of the brain responsible for or affected by changes in CD and LLE. It is found that the wavelet-chaos methodology and the sub-band analysis developed in this research accurately characterizes the non-linear dynamics of non-stationary EEG-like signals with respect to the EEG complexity and chaoticity. It is concluded that changes in the brain dynamics are not spread out equally across the spectrum of the EEG and over the entire brain, but are localized to certain frequency bands and electrode loci. New potential markers of abnormality were discovered in this research for both eyes open and closed conditions.     

A review of prognostic and predictive biomarkers in breast cancer

Clinical and Experimental Medicine - Breast cancer (BC) is a common cancer all over the world that affects women. BC is one of the leading causes of cancer mortality in women, which today has...